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Using Gen AI in Testing: Tariq's King opinion

17 Кві 2024

Brightest

In today's tech and career landscape, generative AI is a game-changer, revolutionizing system adaptability and accessibility. But alongside its promise, ethical concerns loom large, urging responsible usage.

We asked Tariq King, an international keynote speaker and expert in AI and testing, some of the most urging questions regarding using Generative AI in Testing.

 

Can you explain the significance of generative AI in today's technological landscape and its potential applications?

Today's technological landscape is all about implementing the next generation of systems that are easy to use, seamlessly integrate with other systems, and dynamically adapt to changing conditions and user needs. Generative AI is perhaps the most significant advancement towards making these types of systems a reality. Advancements with large language models have made AI capabilities both highly accessible and produced what I like to refer to as believable AI systems that anyone can engage with using natural language.

 

When discussing Generative AI, often many ethical considerations come to mind. What do you think about this topic?

With AI systems, ethics must be treated as both a design and runtime testing concern. Things that come to mind immediately are considerations such as AI fairness and making sure that these systems do not cause harm to groups that may already be at a disadvantage. This technology is in our homes, workplaces, and everywhere else and so we must think about the possible negative social and cultural impacts generative AI could have on us as people. For me, this is the part where AI needs to become more humanized and we need to make sure there is adequate governance so that it is used responsibly.

 

How do you envision the role of Generative AI Test Engineers evolving alongside advancements in generative AI, and what career development opportunities could you imagine in this field?

Generative AI is creating a whole new world for test engineers to thrive in. It can be leveraged to help make software testing professionals more productive by assisting with tasks including test planning and optimization, test generation, test reporting, test maintenance, migration, and more. I believe that it also provides a platform of experimentation where we can collaborate with the machines to be more creative with our testing. We always talk about testing smarter, not harder. Using these machines to generate new testing ideas, or tailor existing ones to new scenarios makes this an exciting time to be a tester! Testers are also the best candidates to use this technology in the right way since they bring their critical thinking, risk analysis, and other problem-solving skills to the table to question the AI and guide it toward the best result possible.

 


Having in mind that testing tasks will never look the same as before, with the boom of the latest AI tools, Tariq King teamed up with Rahul Verma, Girish Nuli, Vipul Kocher, and José Díaz on a fully interactive Certified Generative AI-Assisted Test Engineer (GenAIA-TE) course from Artificial Intelligence United.

This certification emphasizes hands-on practice in formulating prompts to guide large language models (LLMs) in all types of software testing activities. The interesting thing is that it allows us to scale a practitioner-based teaching philosophy.

👉 If you want to become a trainer and add this certification to your portfolio, the first train-the-trainer (TTT) session takes place on April 22-24 with yours truly and Rahul Verma.

👉  If you are a professional and want to take this course or have your team take it, join our waiting list to receive information about updates and when the first course is open for registration!